Abstract
This paper introduces a solution for detecting humans in smart spaces through computer vision. The approach is valid both for images in visible and infrared spectra. Histogram of oriented gradients (HOG) is used for feature extraction in the human detection process, whilst linear support vector machines (SVM) are used for human classification. A set of tests is conducted to find the classifiers which optimize recall in the detection of persons in visible video sequences. Then, the same classifiers are used to detect people in infrared video sequences obtaining excellent results.
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Tribaldos, P., Serrano-Cuerda, J., López, M.T., Fernández-Caballero, A., López-Sastre, R.J. (2013). People Detection in Color and Infrared Video Using HOG and Linear SVM. In: Ferrández Vicente, J.M., Álvarez Sánchez, J.R., de la Paz López, F., Toledo Moreo, F.J. (eds) Natural and Artificial Computation in Engineering and Medical Applications. IWINAC 2013. Lecture Notes in Computer Science, vol 7931. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38622-0_19
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DOI: https://doi.org/10.1007/978-3-642-38622-0_19
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